class_docstr: The QM7b dataset from the `"MoleculeNet: A Benchmark for Molecular
  Machine Learning" <https://arxiv.org/abs/1703.00564>`_ paper, consisting of
  7,211 molecules with 14 regression targets.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      transform (callable, optional): A function/transform that takes in an
          :obj:`torch_geometric.data.Data` object and returns a transformed
          version. The data object will be transformed before every access.
          (default: :obj:`None`)
      pre_transform (callable, optional): A function/transform that takes in
          an :obj:`torch_geometric.data.Data` object and returns a
          transformed version. The data object will be transformed before
          being saved to disk. (default: :obj:`None`)
      pre_filter (callable, optional): A function that takes in an
          :obj:`torch_geometric.data.Data` object and returns a boolean
          value, indicating whether the data object should be included in the
          final dataset. (default: :obj:`None`)
      force_reload (bool, optional): Whether to re-process the dataset.
          (default: :obj:`False`)
  
  **STATS:**
  
  .. list-table::
      :widths: 10 10 10 10 10
      :header-rows: 1
  
      * - #graphs
        - #nodes
        - #edges
        - #features
        - #tasks
      * - 7,211
        - ~15.4
        - ~245.0
        - 0
        - 14
code: def __init__(
      self,
      root: str,
      transform: Optional[Callable] = None,
      pre_transform: Optional[Callable] = None,
      pre_filter: Optional[Callable] = None,
      force_reload: bool = False,
  ) -> None:
      super().__init__(
          root,
          transform,
          pre_transform,
          pre_filter,
          force_reload=force_reload,
      )
      self.load(self.processed_paths[0])
  
file_path: pytorch_geometric/torch_geometric/datasets/qm7.py
imports: from typing import Callable, Optional
  import torch
  from torch_geometric.data import Data, InMemoryDataset, download_url
label_desc: Use image node_id 1 to create a new QM7b object from inherited base classes: InMemoryDataset with example: obj = QM7b(root, transform, pre_transform, pre_filter, force_reload)